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Motion correction using an enhanced floating navigator and GRAPPA operations
Author(s) -
Lin Wei,
Huang Feng,
Börnert Peter,
Li Yu,
Reykowski Arne
Publication year - 2010
Publication title -
magnetic resonance in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 1.696
H-Index - 225
eISSN - 1522-2594
pISSN - 0740-3194
DOI - 10.1002/mrm.22200
Subject(s) - computer science , imaging phantom , computer vision , weighting , motion (physics) , artificial intelligence , rotation (mathematics) , orientation (vector space) , motion compensation , encoding (memory) , translation (biology) , line (geometry) , flexibility (engineering) , physics , mathematics , optics , acoustics , biochemistry , chemistry , geometry , messenger rna , gene , statistics
A method for motion correction in multicoil imaging applications, involving both data collection and reconstruction, is presented. The floating navigator method, which acquires a readout line off center in the phase‐encoding direction, is expanded to detect translation/rotation and inconsistent motion. This is done by comparing floating navigator data with a reference k ‐space region surrounding the floating navigator line, using a correlation measure. The technique of generalized autocalibrating partially parallel acquisition is further developed to correct for a fully sampled, motion‐corrupted dataset. The flexibility of generalized autocalibrating partially parallel acquisition kernels is exploited by extrapolating readout lines to fill in missing “pie slices” of k ‐space caused by rotational motion and regenerating full k ‐space data from multiple interleaved datasets, facilitating subsequent rigid‐body motion correction or proper weighting of inconsistent data (e.g., with through‐plane and nonrigid motion). Phantom and in vivo imaging experiments with turbo spin‐echo sequence demonstrate the correction of severe motion artifacts. Magn Reson Med, 2010. © 2009 Wiley‐Liss, Inc.